Analytics Manager (Ecommerce) - up to £65,000
I am currently working with a Global E-commerce enterprise that was a pioneer in the dot com boom.
They are investing heavily in analytics and as such they are seeking an experienced Analytics Manager with extensive experience in customer analytics to join their team. The Advanced Analytics is a newly formed group- one that is key to the strategic direction of the company!
Advanced Analytics will utilize sophisticated statistical analysis and machine learning to work across business areas such as Marketing Analytics, Customer Insights & Analysis, Call Centre Analytics, Product Analytics, Pricing Optimization, Recommendation Engines, Personalization, etc.
You will have the opportunity to play a critical role in shaping the road ahead for my client!
· Pricing and yield management experience a strong plus; partner with Pricing team: leverage advanced analytics for Pricing Optimization and to inform pricing tests
· Understand the Customer Lifecycle; generate actionable insights and recommendations to ultimately increase ARPU (Average Revenue Per User)
· Develop statistical methodologies to predict customer behaviour and prescribe best course of action
· Uncover key customer segmentation and associated behavioural analyses
· Derive accurate customer Lifetime Value (LTV) and inform business decisions using an LTV lens
· Apply machine learning to build recommendation engines (eg: Marketing Personalization)
· Build new Products & Services for our customers, driven by Data Science
· Help our Customers understand better and engage more effectively with their own customer base (via segmentation insights, reports, new products, generated recommendations, etc.)
· Establish a culture of rapid experimentation by being a 'go to expert'
· MS/PhD in a quantitative discipline: Statistics, Math, Computer Science, Operations Research, etc.
· 5+ years of industry experience with Advanced Analytics
· Expertise in statistical modelling/ machine learning; Text/Sentiment Analysis a plus
· Ability to analyse structured & unstructured/semi-structured data
· Proficiency in SQL and a statistical analysis tool such as R or SAS; Python expertise a big plus.
· Experience with accessing and manipulating data in Hadoop/Hive; Spark experience a plus
· Demonstrated ability to build large-scale predictive models with real-world data.